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Carboplatin and cisplatin are chemotherapeutic agents that are used extensively for treating epithelial ovarian cancer. These drugs can be highly effective, yet tumors are frequently refractory to treatment or become resistant upon tumor relapse. Epigenetic silencing, particularly at promoter regions of genes regulates important cell function and has been associated with all stages of tumor formation and progression and may contribute to therapy response. We analyzed the epigenome of 50 primary ovarian tumors and 12 normal ovarian samples using an array based method previously developed in our lab and associated Affymetrix U133 expression data. We then identified gene candidates that segregate patients based on platinum sensitivity and patient survival. These candidates were then pooled into a genome-wide RNAi-based screen where we validated a gene encoding a chromatin remodeling protein, CHD3, a member of the Mi-2 NuRD complex, and show that it is linked to chemoresistance. CHD3 is silenced through an epigenetic mechanism in both ovarian cancer cell lines and primary ovarian tumors. When ovarian cancer cell lines that are transcriptionally silenced for CHD3 are challenged with carboplatin they display a striking slow growth phenotype as well as increased resistance to the chemotherapy drugs carboplatin and cisplatin. Taken together, we provide the first evidence for a role for CHD3 as an important mediator of chemoresistance in ovarian cancer. Furthermore, CHD3 might represent a response predictor and potential therapeutic target for predicting chemoresistance in this disease.

Background The use of next generation RNA sequencing (RNA-seq) allows for the characterization of the transcriptome at levels of detail unachievable by array-based technologies. RNA-seq analysis can quantify expression of novel transcripts and alternatively spliced isoforms in addition to known genes. Alternative splicing allows for flexibility in production of protein isoforms and is frequently dysregulated in cancer. As splice variants may play a role in response to therapy (Solier, et al, Cancer Res., 2010), we studied differential gene and isoform expression in breast cancers after one dose of treatment, prior to a course of preoperative therapy. Methods: We sequenced transcriptomes of core biopsy samples from 8 breast cancer patients enrolled in a preoperative clinical trial using trastuzumab (HER2 positive) or bevacizumab (HER2 negative) with chemotherapy. Tumor core biopsies were taken before and after 10 days of either biologic or nab-paclitaxel treatment and stored in OCT compound. Total RNA was extracted, amplified and libraries were constructed for the 16 samples using TruSeq (Illumina). Paired-end sequencing was performed on the Illumina GAII platform with read length of 74bp. Sequence data was mapped using TopHat and transcript abundance in FPKM units (Fragments per kilo-base of mRNA per million reads) estimated for a total of 22,160 unique genes and 34,449 unique transcripts from RefSeq. Differential expression of transcripts between baseline and 10-day samples was estimated using t-statistics with read-counts modeled as a Poisson distribution. Differentially expressed transcripts were selected at a significance level of 0.05 after multiple testing correction. Results: Each sample had on average 46 million paired-end reads, of which on average 70% were mappable to the human reference genome (UCSC, hg19). A median of 138 (range 68–948) transcripts varied with treatment. GO analysis showed enrichment of cell-adhesion, apoptosis, differentiation and cell proliferation pathways. Interestingly, the isoforms of several known cancer genes such as TP53 were seen in all treatment types. Certain isoforms were only seen to change upon brief exposure to chemotherapy such as BCL2 whereas TNF ligand and PCDH isoforms showed significant change only with biologic agents. Conclusions: These results suggest that recurrent changes in both canonical genes and splice variants occur over the course of treatment in early breast cancer. This underscores the value of RNA-seq to provide novel information that may be clinically useful. Brief exposure to monotherapy prior to combination treatment may provide important mechanistic insights and produce predictive biomarkers. Biologic treatments may produce unique changes that can only be discovered with novel next generation sequencing techniques. Citation Information: Cancer Res 2011;71(24 Suppl):Abstract nr P3-06-01.